The International Maritime Organization (IMO) is a specialized United Nations (UN) agency regulating maritime transport. One of the very hot topics currently on the IMO agenda is decarbonization. In that regard, the IMO decided in 2018 to achieve by 2050 a reduction of at least 50% in maritime green house gas (GHG) emissions vis-à-vis 2008 levels. The purpose of this paper is to discuss the possible role of Market Based Measures (MBMs) so as to achieve the above target. To that effect, a brief discussion of MBMs at the IMO and the EU is presented, and a possible way forward is proposed, focusing on a bunker levy.
Global climate change, which is largely attributed to human activity, is one of the foremost challenges of the 21st century. In recent times, there have been notable alterations in the Earth's climate, resulting in profound impacts on ecosystems and biodiversity. These alterations are caused by greenhouse gas, such as carbon dioxide, methane, and nitrous oxide. Greenhouse gas emissions are caused by practices such as deforestation, industrial operations, and the combustion of fossil fuels in vehicles, vessels, aircraft, and manufacturing facilities. The maritime and aviation industry is currently responsible for approximately 6% of global greenhouse gas emissions. Due to logistical and economic constraints, these industries are heavily reliant on liquid fuels, making direct electrification options unavailable for large parts of these sectors. As a result, these sectors are considered ‘hard to abate’. Understanding the future climate mitigation challenges associated with the maritime and aviation sectors is crucial in shaping effective policy measures, avoiding stranded assets, and preserving the chance to meet Paris Agreement-compatible emission reduction pathways.
This thesis identifies three main challenges and proposes modelling approaches to address them when modelling decarbonization pathways for the aviation and maritime sectors. From these challenges, research gaps have been identified that this PhD thesis aims to fill. Three models have been developed for the thesis: a maritime optimization model, a maritime demand model, and an aviation demand model. The modelling landscape and methodology vary across models, ranging from econometrics and data science to mathematical optimization.
To overcome the challenges and fill in the research gaps, three corresponding modelling approaches have been successfully applied:
1. Developing a holistic decarbonization modelling landscape. This includes life-cycle representations of technology costs and emissions, the upscaling of bottleneck technologies, the availability of sustainable biomass, and consideration of competing demand from other industries, as well as representations of policy levers such as carbon pricing or improvements to fuel efficiency.
2. Developing demand models that interpret the underlying scenario narrative consistently (SSP framework).
3. Improving the representation of technological learning for low-carbon technologies in energy system models.
The findings acquired by applying these three modelling approaches are valuable for energy modellers, climate scientists, and policymakers and offer unique insights into the inherent system dynamics associated with decarbonization of hard-to-abate sectors. Utilizing this modelling landscape reveals that current decarbonization efforts for hard-to-abate sectors are insufficient.
Since the outbreak of COVID-19, its impacts on the maritime transportation and logistics field have been multi-dimensional. In addition to the green shipping corridor proposed by the Clydebank Declaration in the United Kingdom in 2021, port digitalisation and decarbonisation of the maritime industry have become focal issues in the field. The industry needs a new framework to offset the negative impacts of the pandemic and to accommodate integrated technologies comprising of artificial intelligence (AI), blockchain, cloud systems, internet of things (IoT) and others, which have been applied to the industry. Having considered these circumstances, this paper aims to propose the 6th-generation ports model with smart port (6GP) as a new framework for the port logistics industry in the post-COVID-19 period. The proposed 6GP contributes to providing business development strategy and port development policy for stakeholders in the industry in the post-pandemic era reflecting focal challenges such as digitalisation, decarbonisation, sustainability and smart transformation. It also contributes to expanding port devolution theory from the fifth-generation ports (5GP) to 6GP.
Global marine shipping annually accounts for about one billion tonnes of CO2 equivalent greenhouse gas emissions. Nuclear power propulsion may be an option to de-carbonise some niches of the merchant ocean fleet. This paper considers the three experimental nuclear-powered merchant ships launched and operated in the world so far; the iconic Savannah (USA), Otto Hahn (West Germany) and Mutsu (Japan). They were independently developed and operated in the 1960s and 1970s for technology demonstration and learning. A fourth ship, Sevmorput (Soviet Union/Russia, 1988–to date), is a pioneer in respect of its logistics functions and propulsion system. This paper develops a theoretical framework for the sustainability assessment of nuclear propulsion in ocean merchant shipping and presents a method for exploring nuclear propulsion, relative to flag state, ports, shipping resources and ocean transport services. The experimental ships’ transport efficiency is discussed and related to contemporary oil-fired shipping of general cargo, and to recent literature presenting possible future applications of merchant nuclear propulsion in some market niches. Insights provided include: (1) the experiments demonstrate that merchant nuclear propulsion may be technically feasible; (2) port and canal access for merchant nuclear-powered ships may be difficult and restricted; (3) the up-front costs, refuelling and end-of-life decommissioning costs of nuclear-powered ships are vast and uncertain against conventionally-powered ships; (4) because nuclear fuel is comparatively low-cost, the conventional oil-fired ship cost implications of high-speed operations do not apply.
Benchmarking the energy efficiency of ships is not a straightforward task, mainly due to the diversity of operations. Although driving cycles have been used for decades in evaluating the performance of road vehicles, these do not exist in formal policy-making for maritime transport. This work builds on a previously proposed methodology. It uses noon reports of 327 vessels for 2019 to construct operational cycles for seven size classes of container ships using the main engine power as the main parameter. Concerning the main engine emissions, the resulting cycles reduce variation in the carbon intensity indicator values by more than 30% while maintaining an average accuracy of 97.7% in absolute emissions. These figures show that the concept can improve operational carbon intensity indicators in terms of robustness and their technical counterparts in optimizing ship design. The paper also proposes further work required for benchmarking applications in policy-making.
Operational cycles for maritime transportation is a new concept to improve the assessment of ships’ energy efficiency and offer benchmarking options among similar ship types and sizes. This work extends previous research to consolidate the methodology, bring more comprehensiveness, and provide a more holistic assessment of these operational cycles. The cycles are designed from noon reports from a fleet of around 300 container ships divided into eight size groups. The comparison between cycles derived from speed and draft with those based on main engine power identifies that the cycles based on speed and draft are more accurate and allow for estimating the Energy Efficiency Operational Index but require more data. The main-engine-power cycles are more effective in benchmarking through the Annual Efficiency Ratio. These cycles reduce the inherent variability of the carbon intensity indicator and present good opportunities as a benchmarking tool for strengthening the regulatory framework of international shipping.
This scientific study aims to compare the significance of onboard positioning of two different classes of wind propulsion systems for retrofit installations to maximize fuel and emissions savings. The study focuses on comparing the performance a low lift-to-drag ratio wind propulsion system, the Rotor Sail, and a high lift-to-drag ratio one, the DynaRig, installed at different places on a real 84000 DWT bulk carrier ship to identify the most efficient placement of these two distinct systems to achieve maximum fuel efficiency. The investigation involves a comprehensive analysis of available deck spaces, and performance prediction program modeling is employed to estimate potential fuel savings for a typical route followed by the vessel. The results show that placing the WPS far forward, close to the hydrodynamic centre of lateral resistance, results in overall higher savings. Both WPS classes see a penalty when placed far from the hydrodynamic centre of lateral resistance, reducing their overall savings potential. However, Rotor Sails are more adversely affected due to their enhanced side force generation per unit thrust. Consequently, the placement of Rotor Sails becomes crucial, especially under upwind conditions, while DynaRigs prove more versatile for installations in the aft. This research provides valuable insights into enhancing the ship's energy efficiency and reducing its environmental impact in the maritime industry.
Bornholm plays a central role in the future offshore power expansion in the
Baltic Sea and as a node between future interconnections between countries. The
necessity to store/convert surplus power puts Bornholm in position to be the first
natural energy hub. Bornholm can be not only the centre for electrical equipment
such as substations but also a centre for P-2-X production from offshore wind power.
The production of electrofuels through P-2-X technologies can penetrate the
transport sector in Bornholm, the hardest to decarbonise, starting with the highspeed ferries to Ystad and Køge, which use in Rønne Havn as their base. The
needs to comply with existing and imminent stricter regulations create the
necessity for an immediate transition, before a fleet renewal. Therefore, this study
investigates the conversion of the hydrogen, produced using offshore wind
electricity, into methanol, whose use as a fuel is mature and does not require
substantial changes to the fleet.
The maritime sector is a key asset for the world economy, but its environmental impact represents a major concern. The sector is primarily supplied with Heavy Fuel Oil, which results in high pollutant emissions. The sector has set targets for deacrbonisation, and alternative fuels have been identified as a short-to medium-term option. The paper addresses the complexity related to the activities of the maritime industry, and discusses the possible contribution of alternative fuels. A sector segmentation is proposed to define the consumption of each sub-segment, so to compare it with the current alternative fuel availability at European level. The paper shows that costs and GHG savings are fundamental enablers for the uptake of alternative fuels, but other aspects are also crucial: technical maturity, safety regulation, expertise needed, etc. The demand for alternative fuels has to be supported by an existing, reliable infrastructure, and this is not yet the case for many solutions (i.e. electricity, hydrogen or methanol). Various options are already available for maritime sector, but the future mix of fuels used will depend on technology improvements, availability, costs and the real potential for GHG emissions reduction.
Wind Propulsion Systems (WPS) have gained significant attention as a means of decarbonizing shipping. Limitations in available deck space, emissions reduction targets, and regulatory compliance have led to a wide array of potential WPS configurations, each exhibiting distinct aerodynamic performance and requiring unique optimum sail trims for each unit due to complex interactions. This variability challenges existing aerodynamic models and optimization efforts for maximizing fuel savings. To address this, we present a novel methodology that, for the first time in WPS aerodynamic performance prediction, combines Computational Fluid Dynamics (CFD), independent sail trim optimization, and Machine Learning (ML) to develop surrogate models — Gaussian Process Regression and Feedforward Neural Networks — that rapidly predict aerodynamic performance with CFD-equivalent accuracy. These surrogates capture aerodynamic interactions across various WPS configurations, including unit number, deck arrangement, independent sail trim, hull characteristics, and wind conditions. While employing established ML techniques, our approach is novel in its resource-efficient generation of a comprehensive aerodynamic database, derived from the first in-depth independent trim optimization of a DynaRig case study. Our approach enables the modeling of complex, non-linear interactions that traditional interpolation methods fail to capture. Results show that the developed surrogate models achieve CFD-level accuracy, with an average error below 1 while significantly reducing computational time. This ML-enhanced framework facilitates extensive, rapid WPS design optimizations, supporting efficient integration into performance prediction programs (PPPs) and maximizing fuel savings and emissions reductions tailored to specific routes and wind conditions.Machine Learning; CFD-Simulations; Aerodynamic Performance; Wind Propulsion Systems; Green Shipping; Independent Sail Trim Optimization.